Overview

Dataset statistics

Number of variables17
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)7.3%
Total size in memory7.7 KiB
Average record size in memory144.0 B

Variable types

Categorical2
Text3
Numeric12

Alerts

Dataset has 4 (7.3%) duplicate rowsDuplicates
Excellent is highly overall correlated with Very good and 5 other fieldsHigh correlation
Very good is highly overall correlated with Excellent and 9 other fieldsHigh correlation
Average is highly overall correlated with Excellent and 8 other fieldsHigh correlation
Poor is highly overall correlated with Excellent and 9 other fieldsHigh correlation
Terrible is highly overall correlated with Excellent and 9 other fieldsHigh correlation
Excellent_ratio is highly overall correlated with Very good and 9 other fieldsHigh correlation
VG_ratio is highly overall correlated with Very good and 9 other fieldsHigh correlation
Average_ratio is highly overall correlated with Very good and 9 other fieldsHigh correlation
Poor_ratio is highly overall correlated with Excellent and 10 other fieldsHigh correlation
Terrible_ratio is highly overall correlated with Very good and 8 other fieldsHigh correlation
Tripadvisor rank is highly overall correlated with ExcellentHigh correlation
City is highly overall correlated with Excellent_ratio and 4 other fieldsHigh correlation
Score is highly overall correlated with Very good and 8 other fieldsHigh correlation
Very good has 5 (9.1%) zerosZeros
Average has 21 (38.2%) zerosZeros
Poor has 23 (41.8%) zerosZeros
Terrible has 22 (40.0%) zerosZeros
VG_ratio has 5 (9.1%) zerosZeros
Average_ratio has 21 (38.2%) zerosZeros
Poor_ratio has 23 (41.8%) zerosZeros
Terrible_ratio has 22 (40.0%) zerosZeros

Reproduction

Analysis started2023-08-01 16:08:04.528642
Analysis finished2023-08-01 16:08:22.414190
Duration17.89 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

City
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size880.0 B
Paris
27 
Cairo
24 
Seoul

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters275
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCairo
2nd rowCairo
3rd rowCairo
4th rowCairo
5th rowCairo

Common Values

ValueCountFrequency (%)
Paris 27
49.1%
Cairo 24
43.6%
Seoul 4
 
7.3%

Length

2023-08-01T19:08:22.467846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-01T19:08:22.579920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
paris 27
49.1%
cairo 24
43.6%
seoul 4
 
7.3%

Most occurring characters

ValueCountFrequency (%)
a 51
18.5%
r 51
18.5%
i 51
18.5%
o 28
10.2%
P 27
9.8%
s 27
9.8%
C 24
8.7%
S 4
 
1.5%
e 4
 
1.5%
u 4
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 220
80.0%
Uppercase Letter 55
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 51
23.2%
r 51
23.2%
i 51
23.2%
o 28
12.7%
s 27
12.3%
e 4
 
1.8%
u 4
 
1.8%
l 4
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
P 27
49.1%
C 24
43.6%
S 4
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 275
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 51
18.5%
r 51
18.5%
i 51
18.5%
o 28
10.2%
P 27
9.8%
s 27
9.8%
C 24
8.7%
S 4
 
1.5%
e 4
 
1.5%
u 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 51
18.5%
r 51
18.5%
i 51
18.5%
o 28
10.2%
P 27
9.8%
s 27
9.8%
C 24
8.7%
S 4
 
1.5%
e 4
 
1.5%
u 4
 
1.5%

Name
Text

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size880.0 B
2023-08-01T19:08:22.759337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length134
Median length34
Mean length23.963636
Min length8

Characters and Unicode

Total characters1318
Distinct characters72
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)85.5%

Sample

1st rowTrans travel
2nd rowTrans travel
3rd rowSahara Travel
4th rowEgypt Tour Guide - Mina Samir
5th rowPyramids Land Private Tours
ValueCountFrequency (%)
tours 18
 
8.6%
egypt 12
 
5.7%
musee 10
 
4.8%
de 9
 
4.3%
6
 
2.9%
tour 6
 
2.9%
private 5
 
2.4%
guide 5
 
2.4%
paris 4
 
1.9%
and 3
 
1.4%
Other values (113) 132
62.9%
2023-08-01T19:08:23.103094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
 
11.8%
e 113
 
8.6%
a 103
 
7.8%
r 91
 
6.9%
s 81
 
6.1%
o 68
 
5.2%
i 67
 
5.1%
u 64
 
4.9%
t 55
 
4.2%
n 48
 
3.6%
Other values (62) 473
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 934
70.9%
Uppercase Letter 184
 
14.0%
Space Separator 155
 
11.8%
Other Letter 19
 
1.4%
Other Punctuation 15
 
1.1%
Dash Punctuation 8
 
0.6%
Decimal Number 2
 
0.2%
Final Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 113
12.1%
a 103
11.0%
r 91
9.7%
s 81
8.7%
o 68
 
7.3%
i 67
 
7.2%
u 64
 
6.9%
t 55
 
5.9%
n 48
 
5.1%
d 43
 
4.6%
Other values (18) 201
21.5%
Uppercase Letter
ValueCountFrequency (%)
T 30
16.3%
M 25
13.6%
E 19
10.3%
P 16
8.7%
C 15
8.2%
A 13
7.1%
S 11
 
6.0%
G 11
 
6.0%
D 6
 
3.3%
L 6
 
3.3%
Other values (11) 32
17.4%
Other Letter
ValueCountFrequency (%)
2
 
10.5%
2
 
10.5%
2
 
10.5%
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (5) 5
26.3%
Other Punctuation
ValueCountFrequency (%)
, 11
73.3%
2
 
13.3%
' 2
 
13.3%
Decimal Number
ValueCountFrequency (%)
7 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1118
84.8%
Common 181
 
13.7%
Katakana 18
 
1.4%
Hiragana 1
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 113
 
10.1%
a 103
 
9.2%
r 91
 
8.1%
s 81
 
7.2%
o 68
 
6.1%
i 67
 
6.0%
u 64
 
5.7%
t 55
 
4.9%
n 48
 
4.3%
d 43
 
3.8%
Other values (39) 385
34.4%
Katakana
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
155
85.6%
, 11
 
6.1%
- 8
 
4.4%
2
 
1.1%
' 2
 
1.1%
1
 
0.6%
7 1
 
0.6%
1 1
 
0.6%
Hiragana
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1289
97.8%
Katakana 18
 
1.4%
None 9
 
0.7%
Punctuation 1
 
0.1%
Hiragana 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
 
12.0%
e 113
 
8.8%
a 103
 
8.0%
r 91
 
7.1%
s 81
 
6.3%
o 68
 
5.3%
i 67
 
5.2%
u 64
 
5.0%
t 55
 
4.3%
n 48
 
3.7%
Other values (42) 444
34.4%
None
ValueCountFrequency (%)
é 5
55.6%
2
 
22.2%
è 1
 
11.1%
ô 1
 
11.1%
Katakana
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (4) 4
22.2%
Punctuation
ValueCountFrequency (%)
1
100.0%
Hiragana
ValueCountFrequency (%)
1
100.0%
Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size880.0 B
2023-08-01T19:08:23.381311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length589
Median length424
Mean length371.61818
Min length101

Characters and Unicode

Total characters20439
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)85.5%

Sample

1st row['memphis tours', 'tour consultant', 'nile cruise', 'wonderful trip', 'travel experience', 'abu simbel', 'dead sea', 'incredible experience', 'egyptian museum', 'every step of the way', 'private tour', 'amazing tour', 'nubian village', 'visit egypt', 'made us feel', 'kom ombo', 'cairo airport', 'always on time', 'his team', 'luxor temple', 'wonderful guide', 'day tour', 'his knowledge', 'felt safe', 'ancient egypt', 'afifi', 'yasmeen', 'itinerary', 'company', 'driver']
2nd row['memphis tours', 'tour consultant', 'nile cruise', 'wonderful trip', 'travel experience', 'abu simbel', 'dead sea', 'incredible experience', 'egyptian museum', 'every step of the way', 'private tour', 'amazing tour', 'nubian village', 'visit egypt', 'made us feel', 'kom ombo', 'cairo airport', 'always on time', 'his team', 'luxor temple', 'wonderful guide', 'day tour', 'his knowledge', 'felt safe', 'ancient egypt', 'afifi', 'yasmeen', 'itinerary', 'company', 'driver']
3rd row['tour manager', 'memphis tours', 'nile cruise', 'egyptian museum', 'ahmed osman', 'made us feel', 'abu simbel', 'egypt trip', 'amazing trip', 'cairo airport', 'his passion', 'ancient egypt', 'private tour', 'went smoothly', 'an amazing guide', 'travel company', 'wealth of knowledge', 'special thanks', 'through customs', 'every step', 'the entire trip', 'papyrus shop', 'national museum', 'once in a lifetime', 'answered all of our questions', 'his team', 'took great care', 'day tour', 'amazing country', 'always felt safe']
4th row['his team', 'excellent photographer', 'photography skills', 'his knowledge', 'amazing photos', 'cabin crew', 'made us feel', 'papyrus museum', 'solo trip', 'always on time', 'our entire trip', 'taking photos', 'amazing trip', 'giza pyramids', 'arranged everything', 'taking care', 'great guide', 'visit cairo', 'felucca ride', 'answered all our questions', 'nile cruise', 'spent days', 'felt very safe', 'beautiful country', 'ancient history', 'falafel', 'great pyramid', 'samir', 'airport', 'egypt']
5th row['egyptian museum', 'takes great pictures', 'skilled driver', 'great tour', 'nice guide', 'essential oils', 'ride camels', 'long layover', 'would highly recommend this tour', 'crazy cairo', 'buy souvenirs', 'booked this tour', 'ancient egypt', 'excellent driver', 'egyptian experience', 'papyrus shop', 'answered all our questions', 'day tour', 'great knowledge', 'cairo tour', 'gouda', 'hoka', 'rasha', 'bazaar', 'pyramids', 'sites', 'mahmoud', 'abu', 'pharmacy', 'egyptologist']
ValueCountFrequency (%)
tour 78
 
3.3%
museum 75
 
3.2%
great 41
 
1.7%
trip 36
 
1.5%
guide 33
 
1.4%
egypt 31
 
1.3%
knowledge 27
 
1.1%
his 27
 
1.1%
the 26
 
1.1%
day 25
 
1.1%
Other values (786) 1975
83.2%
2023-08-01T19:08:23.841439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 2687
13.1%
2319
 
11.3%
e 1646
 
8.1%
, 1292
 
6.3%
a 1166
 
5.7%
i 1163
 
5.7%
r 1084
 
5.3%
t 1077
 
5.3%
s 931
 
4.6%
o 902
 
4.4%
Other values (22) 6172
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14017
68.6%
Other Punctuation 3993
 
19.5%
Space Separator 2319
 
11.3%
Close Punctuation 55
 
0.3%
Open Punctuation 55
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1646
11.7%
a 1166
 
8.3%
i 1163
 
8.3%
r 1084
 
7.7%
t 1077
 
7.7%
s 931
 
6.6%
o 902
 
6.4%
n 826
 
5.9%
l 712
 
5.1%
u 658
 
4.7%
Other values (16) 3852
27.5%
Other Punctuation
ValueCountFrequency (%)
' 2687
67.3%
, 1292
32.4%
" 14
 
0.4%
Space Separator
ValueCountFrequency (%)
2319
100.0%
Close Punctuation
ValueCountFrequency (%)
] 55
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14017
68.6%
Common 6422
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1646
11.7%
a 1166
 
8.3%
i 1163
 
8.3%
r 1084
 
7.7%
t 1077
 
7.7%
s 931
 
6.6%
o 902
 
6.4%
n 826
 
5.9%
l 712
 
5.1%
u 658
 
4.7%
Other values (16) 3852
27.5%
Common
ValueCountFrequency (%)
' 2687
41.8%
2319
36.1%
, 1292
20.1%
] 55
 
0.9%
[ 55
 
0.9%
" 14
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 2687
13.1%
2319
 
11.3%
e 1646
 
8.1%
, 1292
 
6.3%
a 1166
 
5.7%
i 1163
 
5.7%
r 1084
 
5.3%
t 1077
 
5.3%
s 931
 
4.6%
o 902
 
4.4%
Other values (22) 6172
30.2%

Score
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size880.0 B
5.0
28 
4.5
26 
4.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters165
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row5.0
2nd row5.0
3rd row5.0
4th row5.0
5th row5.0

Common Values

ValueCountFrequency (%)
5.0 28
50.9%
4.5 26
47.3%
4.0 1
 
1.8%

Length

2023-08-01T19:08:23.976997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-01T19:08:24.078589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
5.0 28
50.9%
4.5 26
47.3%
4.0 1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
. 55
33.3%
5 54
32.7%
0 29
17.6%
4 27
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 110
66.7%
Other Punctuation 55
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 54
49.1%
0 29
26.4%
4 27
24.5%
Other Punctuation
ValueCountFrequency (%)
. 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 55
33.3%
5 54
32.7%
0 29
17.6%
4 27
16.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 55
33.3%
5 54
32.7%
0 29
17.6%
4 27
16.4%

Reviewers#
Real number (ℝ)

Distinct49
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4569.9273
Minimum75
Maximum67052
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:24.185862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile128
Q1296
median902
Q32673.5
95-th percentile20597.8
Maximum67052
Range66977
Interquartile range (IQR)2377.5

Descriptive statistics

Standard deviation11504.813
Coefficient of variation (CV)2.5175047
Kurtosis18.680652
Mean4569.9273
Median Absolute Deviation (MAD)737
Skewness4.1395437
Sum251346
Variance1.3236073 × 108
MonotonicityNot monotonic
2023-08-01T19:08:24.467932image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
535 2
 
3.6%
917 2
 
3.6%
317 2
 
3.6%
467 2
 
3.6%
355 2
 
3.6%
222 2
 
3.6%
1003 1
 
1.8%
4630 1
 
1.8%
2932 1
 
1.8%
3053 1
 
1.8%
Other values (39) 39
70.9%
ValueCountFrequency (%)
75 1
1.8%
104 1
1.8%
114 1
1.8%
134 1
1.8%
135 1
1.8%
137 1
1.8%
147 1
1.8%
149 1
1.8%
150 1
1.8%
165 1
1.8%
ValueCountFrequency (%)
67052 1
1.8%
45890 1
1.8%
27875 1
1.8%
17479 1
1.8%
12949 1
1.8%
12688 1
1.8%
10755 1
1.8%
6213 1
1.8%
4761 1
1.8%
4630 1
1.8%

Excellent
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3225.1455
Minimum73
Maximum53115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:24.617099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile111
Q1218.5
median535
Q31889.5
95-th percentile15017.5
Maximum53115
Range53042
Interquartile range (IQR)1671

Descriptive statistics

Standard deviation8470.4116
Coefficient of variation (CV)2.6263658
Kurtosis23.642033
Mean3225.1455
Median Absolute Deviation (MAD)379
Skewness4.5793284
Sum177383
Variance71747873
MonotonicityNot monotonic
2023-08-01T19:08:24.768255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
535 2
 
3.6%
309 2
 
3.6%
457 2
 
3.6%
338 2
 
3.6%
712 1
 
1.8%
222 1
 
1.8%
2826 1
 
1.8%
2263 1
 
1.8%
1754 1
 
1.8%
1865 1
 
1.8%
Other values (41) 41
74.5%
ValueCountFrequency (%)
73 1
1.8%
100 1
1.8%
104 1
1.8%
114 1
1.8%
131 1
1.8%
132 1
1.8%
134 1
1.8%
140 1
1.8%
142 1
1.8%
149 1
1.8%
ValueCountFrequency (%)
53115 1
1.8%
27772 1
1.8%
21034 1
1.8%
12439 1
1.8%
8608 1
1.8%
8475 1
1.8%
5558 1
1.8%
4718 1
1.8%
2925 1
1.8%
2914 1
1.8%

Very good
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1039.9818
Minimum0
Maximum14082
Zeros5
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:24.891018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median81
Q3571.5
95-th percentile4275.6
Maximum14082
Range14082
Interquartile range (IQR)565.5

Descriptive statistics

Standard deviation2597.759
Coefficient of variation (CV)2.4978889
Kurtosis15.827567
Mean1039.9818
Median Absolute Deviation (MAD)81
Skewness3.8295704
Sum57199
Variance6748351.9
MonotonicityNot monotonic
2023-08-01T19:08:24.994884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 5
 
9.1%
3 4
 
7.3%
1 3
 
5.5%
7 3
 
5.5%
8 2
 
3.6%
17 2
 
3.6%
6 2
 
3.6%
1107 1
 
1.8%
81 1
 
1.8%
358 1
 
1.8%
Other values (31) 31
56.4%
ValueCountFrequency (%)
0 5
9.1%
1 3
5.5%
2 1
 
1.8%
3 4
7.3%
6 2
 
3.6%
7 3
5.5%
8 2
 
3.6%
14 1
 
1.8%
17 2
 
3.6%
33 1
 
1.8%
ValueCountFrequency (%)
14082 1
1.8%
11594 1
1.8%
4907 1
1.8%
4005 1
1.8%
3829 1
1.8%
3682 1
1.8%
3295 1
1.8%
1976 1
1.8%
1725 1
1.8%
1107 1
1.8%

Average
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237.8
Minimum0
Maximum3501
Zeros21
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:25.102953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q3160.5
95-th percentile1183.2
Maximum3501
Range3501
Interquartile range (IQR)160.5

Descriptive statistics

Standard deviation580.89511
Coefficient of variation (CV)2.4427885
Kurtosis18.8484
Mean237.8
Median Absolute Deviation (MAD)10
Skewness3.9694696
Sum13079
Variance337439.13
MonotonicityNot monotonic
2023-08-01T19:08:25.202670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 21
38.2%
10 2
 
3.6%
2 2
 
3.6%
20 1
 
1.8%
41 1
 
1.8%
50 1
 
1.8%
59 1
 
1.8%
150 1
 
1.8%
11 1
 
1.8%
22 1
 
1.8%
Other values (23) 23
41.8%
ValueCountFrequency (%)
0 21
38.2%
1 1
 
1.8%
2 2
 
3.6%
3 1
 
1.8%
6 1
 
1.8%
10 2
 
3.6%
11 1
 
1.8%
15 1
 
1.8%
20 1
 
1.8%
22 1
 
1.8%
ValueCountFrequency (%)
3501 1
1.8%
1722 1
1.8%
1403 1
1.8%
1089 1
1.8%
951 1
1.8%
830 1
1.8%
718 1
1.8%
533 1
1.8%
530 1
1.8%
246 1
1.8%

Poor
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.090909
Minimum0
Maximum352
Zeros23
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:25.312305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q337
95-th percentile289.6
Maximum352
Range352
Interquartile range (IQR)37

Descriptive statistics

Standard deviation87.488681
Coefficient of variation (CV)2.0785648
Kurtosis6.4007526
Mean42.090909
Median Absolute Deviation (MAD)2
Skewness2.6653393
Sum2315
Variance7654.2694
MonotonicityNot monotonic
2023-08-01T19:08:25.410906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 23
41.8%
1 4
 
7.3%
29 2
 
3.6%
19 2
 
3.6%
3 2
 
3.6%
6 2
 
3.6%
82 1
 
1.8%
21 1
 
1.8%
86 1
 
1.8%
26 1
 
1.8%
Other values (16) 16
29.1%
ValueCountFrequency (%)
0 23
41.8%
1 4
 
7.3%
2 1
 
1.8%
3 2
 
3.6%
4 1
 
1.8%
5 1
 
1.8%
6 2
 
3.6%
14 1
 
1.8%
19 2
 
3.6%
21 1
 
1.8%
ValueCountFrequency (%)
352 1
1.8%
336 1
1.8%
333 1
1.8%
271 1
1.8%
169 1
1.8%
152 1
1.8%
86 1
1.8%
82 1
1.8%
67 1
1.8%
62 1
1.8%

Terrible
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.945455
Minimum0
Maximum294
Zeros22
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:25.514177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile191.6
Maximum294
Range294
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation59.588533
Coefficient of variation (CV)2.2966849
Kurtosis9.9250399
Mean25.945455
Median Absolute Deviation (MAD)3
Skewness3.172972
Sum1427
Variance3550.7933
MonotonicityNot monotonic
2023-08-01T19:08:25.610334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 22
40.0%
3 4
 
7.3%
1 4
 
7.3%
11 2
 
3.6%
5 2
 
3.6%
17 2
 
3.6%
13 2
 
3.6%
200 1
 
1.8%
50 1
 
1.8%
28 1
 
1.8%
Other values (14) 14
25.5%
ValueCountFrequency (%)
0 22
40.0%
1 4
 
7.3%
2 1
 
1.8%
3 4
 
7.3%
5 2
 
3.6%
6 1
 
1.8%
8 1
 
1.8%
11 2
 
3.6%
13 2
 
3.6%
17 2
 
3.6%
ValueCountFrequency (%)
294 1
1.8%
211 1
1.8%
200 1
1.8%
188 1
1.8%
95 1
1.8%
50 1
1.8%
47 1
1.8%
43 1
1.8%
41 1
1.8%
35 1
1.8%

Excellent_ratio
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79641313
Minimum0.43264249
Maximum1.0127796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:25.743561image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.43264249
5-th percentile0.48600747
Q10.60803043
median0.93498965
Q30.97834446
95-th percentile1
Maximum1.0127796
Range0.58013707
Interquartile range (IQR)0.37031402

Descriptive statistics

Standard deviation0.19801609
Coefficient of variation (CV)0.24863489
Kurtosis-1.5663627
Mean0.79641313
Median Absolute Deviation (MAD)0.077789905
Skewness-0.33155403
Sum43.802722
Variance0.039210372
MonotonicityNot monotonic
2023-08-01T19:08:25.855549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1 6
 
10.9%
0.9521126761 2
 
3.6%
0.9747634069 2
 
3.6%
0.9785867238 2
 
3.6%
0.4887688985 1
 
1.8%
0.5982264666 1
 
1.8%
0.6108745496 1
 
1.8%
0.7001675042 1
 
1.8%
0.4707870594 1
 
1.8%
0.5960548885 1
 
1.8%
Other values (37) 37
67.3%
ValueCountFrequency (%)
0.432642487 1
1.8%
0.4707870594 1
1.8%
0.4851351351 1
1.8%
0.486381323 1
1.8%
0.4887688985 1
1.8%
0.5110344828 1
1.8%
0.5167828917 1
1.8%
0.5617977528 1
1.8%
0.5721784777 1
1.8%
0.5776053215 1
1.8%
ValueCountFrequency (%)
1.012779553 1
 
1.8%
1 6
10.9%
0.9956427015 1
 
1.8%
0.9933333333 1
 
1.8%
0.990968284 1
 
1.8%
0.9864864865 1
 
1.8%
0.9836423119 1
 
1.8%
0.9785867238 2
 
3.6%
0.9781021898 1
 
1.8%
0.9777777778 1
 
1.8%

VG_ratio
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15637671
Minimum0
Maximum0.4507772
Zeros5
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:25.977757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.019514216
median0.057556936
Q30.2911668
95-th percentile0.37244051
Maximum0.4507772
Range0.4507772
Interquartile range (IQR)0.27165258

Descriptive statistics

Standard deviation0.14645199
Coefficient of variation (CV)0.93653331
Kurtosis-1.6181326
Mean0.15637671
Median Absolute Deviation (MAD)0.057556936
Skewness0.27679185
Sum8.6007188
Variance0.021448186
MonotonicityNot monotonic
2023-08-01T19:08:26.090314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 5
 
9.1%
0.001869158879 2
 
3.6%
0.02208201893 2
 
3.6%
0.01713062099 2
 
3.6%
0.04788732394 2
 
3.6%
0.3237250554 1
 
1.8%
0.2997953615 1
 
1.8%
0.2859482476 1
 
1.8%
0.2345058626 1
 
1.8%
0.3180428135 1
 
1.8%
Other values (37) 37
67.3%
ValueCountFrequency (%)
0 5
9.1%
0.001869158879 2
 
3.6%
0.006535947712 1
 
1.8%
0.006666666667 1
 
1.8%
0.01050199538 1
 
1.8%
0.01351351351 1
 
1.8%
0.01526717557 1
 
1.8%
0.01713062099 2
 
3.6%
0.02189781022 1
 
1.8%
0.02208201893 2
 
3.6%
ValueCountFrequency (%)
0.4507772021 1
1.8%
0.3774319066 1
1.8%
0.3725701944 1
1.8%
0.3723849372 1
1.8%
0.3648648649 1
1.8%
0.3464566929 1
1.8%
0.3370786517 1
1.8%
0.3237250554 1
1.8%
0.32 1
1.8%
0.3180428135 1
1.8%

Average_ratio
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.034877302
Minimum0
Maximum0.13359086
Zeros21
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:26.192649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0049333991
Q30.061576491
95-th percentile0.1054143
Maximum0.13359086
Range0.13359086
Interquartile range (IQR)0.061576491

Descriptive statistics

Standard deviation0.039767971
Coefficient of variation (CV)1.140225
Kurtosis-0.68415655
Mean0.034877302
Median Absolute Deviation (MAD)0.0049333991
Skewness0.73339524
Sum1.9182516
Variance0.0015814915
MonotonicityNot monotonic
2023-08-01T19:08:26.369845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 21
38.2%
0.004282655246 2
 
3.6%
0.05509641873 1
 
1.8%
0.1179310345 1
 
1.8%
0.03980582524 1
 
1.8%
0.04985044865 1
 
1.8%
0.06541019956 1
 
1.8%
0.08337965536 1
 
1.8%
0.0394265233 1
 
1.8%
0.08288148722 1
 
1.8%
Other values (24) 24
43.6%
ValueCountFrequency (%)
0 21
38.2%
0.0006301197227 1
 
1.8%
0.001090512541 1
 
1.8%
0.003086419753 1
 
1.8%
0.004140786749 1
 
1.8%
0.004282655246 2
 
3.6%
0.004933399112 1
 
1.8%
0.02568156058 1
 
1.8%
0.0394265233 1
 
1.8%
0.03980582524 1
 
1.8%
ValueCountFrequency (%)
0.1335908579 1
1.8%
0.1179310345 1
1.8%
0.1151187905 1
1.8%
0.1012552301 1
1.8%
0.1010362694 1
1.8%
0.09189189189 1
1.8%
0.08426966292 1
1.8%
0.08337965536 1
1.8%
0.08288148722 1
1.8%
0.07629113097 1
1.8%

Poor_ratio
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0079306781
Minimum0
Maximum0.04361822
Zeros23
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:26.487636image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0019417476
Q30.012016818
95-th percentile0.034665054
Maximum0.04361822
Range0.04361822
Interquartile range (IQR)0.012016818

Descriptive statistics

Standard deviation0.010968807
Coefficient of variation (CV)1.3830857
Kurtosis2.1537166
Mean0.0079306781
Median Absolute Deviation (MAD)0.0019417476
Skewness1.6029762
Sum0.4361873
Variance0.00012031474
MonotonicityNot monotonic
2023-08-01T19:08:26.587115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 23
41.8%
0.001090512541 2
 
3.6%
0.007772020725 1
 
1.8%
0.006733224983 1
 
1.8%
0.0079962808 1
 
1.8%
0.03513513514 1
 
1.8%
0.0157480315 1
 
1.8%
0.02246320682 1
 
1.8%
0.01101928375 1
 
1.8%
0.03446359088 1
 
1.8%
Other values (22) 22
40.0%
ValueCountFrequency (%)
0 23
41.8%
0.0002100399076 1
 
1.8%
0.0004933399112 1
 
1.8%
0.001090512541 2
 
3.6%
0.001941747573 1
 
1.8%
0.002070393375 1
 
1.8%
0.003086419753 1
 
1.8%
0.004966294816 1
 
1.8%
0.006332535331 1
 
1.8%
0.006733224983 1
 
1.8%
ValueCountFrequency (%)
0.04361821986 1
1.8%
0.03793103448 1
1.8%
0.03513513514 1
1.8%
0.03446359088 1
1.8%
0.02246320682 1
1.8%
0.02106430155 1
1.8%
0.02012278308 1
1.8%
0.01894317049 1
1.8%
0.01834261382 1
1.8%
0.0180102916 1
1.8%

Terrible_ratio
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0049853618
Minimum0
Maximum0.033961049
Zeros22
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:26.685890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0025539819
Q30.0069888045
95-th percentile0.019736156
Maximum0.033961049
Range0.033961049
Interquartile range (IQR)0.0069888045

Descriptive statistics

Standard deviation0.0070018835
Coefficient of variation (CV)1.4044886
Kurtosis5.0885094
Mean0.0049853618
Median Absolute Deviation (MAD)0.0025539819
Skewness2.0791984
Sum0.2741949
Variance4.9026373 × 10-5
MonotonicityNot monotonic
2023-08-01T19:08:26.823523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 22
40.0%
0.003154574132 2
 
3.6%
0.01889938855 1
 
1.8%
0.03396104941 1
 
1.8%
0.004288164666 1
 
1.8%
0.01310344828 1
 
1.8%
0.002912621359 1
 
1.8%
0.01296111665 1
 
1.8%
0.01219512195 1
 
1.8%
0.01377410468 1
 
1.8%
Other values (23) 23
41.8%
ValueCountFrequency (%)
0 22
40.0%
0.0004200798152 1
 
1.8%
0.001090512541 1
 
1.8%
0.001480019734 1
 
1.8%
0.001580660158 1
 
1.8%
0.00248447205 1
 
1.8%
0.00255398189 1
 
1.8%
0.002912621359 1
 
1.8%
0.003154574132 2
 
3.6%
0.003629623909 1
 
1.8%
ValueCountFrequency (%)
0.03396104941 1
1.8%
0.02297297297 1
1.8%
0.02168861348 1
1.8%
0.01889938855 1
1.8%
0.01377410468 1
1.8%
0.01310344828 1
1.8%
0.01296111665 1
1.8%
0.01219512195 1
1.8%
0.01146413364 1
1.8%
0.01013096121 1
1.8%

Url
Text

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size880.0 B
2023-08-01T19:08:27.003600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length158
Median length127
Mean length119.23636
Min length98

Characters and Unicode

Total characters6558
Distinct characters61
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)85.5%

Sample

1st rowhttps://www.tripadvisor.com//Attraction_Review-g294201-d17462467-Reviews-Trans_travel-Cairo_Cairo_Governorate.html
2nd rowhttps://www.tripadvisor.com//Attraction_Review-g294201-d17462467-Reviews-Trans_travel-Cairo_Cairo_Governorate.html
3rd rowhttps://www.tripadvisor.com//Attraction_Review-g294201-d16780499-Reviews-Sahara_Travel-Cairo_Cairo_Governorate.html
4th rowhttps://www.tripadvisor.com//Attraction_Review-g294201-d4064603-Reviews-Egypt_Tour_Guide_Mina_Samir-Cairo_Cairo_Governorate.html
5th rowhttps://www.tripadvisor.com//Attraction_Review-g294201-d18313769-Reviews-Pyramids_Land_Private_Tours-Cairo_Cairo_Governorate.html
ValueCountFrequency (%)
https://www.tripadvisor.com//attraction_review-g294201-d17462467-reviews-trans_travel-cairo_cairo_governorate.html 2
 
3.6%
https://www.tripadvisor.com//attraction_review-g294201-d2108429-reviews-cleopatra_egypt_tours-cairo_cairo_governorate.html 2
 
3.6%
https://www.tripadvisor.com//attraction_review-g294201-d3547596-reviews-egypt_tours_club-cairo_cairo_governorate.html 2
 
3.6%
https://www.tripadvisor.com//attraction_review-g294201-d10794410-reviews-private_tour_guides-cairo_cairo_governorate.html 2
 
3.6%
https://www.tripadvisor.com//attraction_review-g294201-d6964370-reviews-my_great_egypt_tours-cairo_cairo_governorate.html 1
 
1.8%
https://www.tripadvisor.com//attraction_review-g294201-d18999846-reviews-amazing_cairo_local_guide_licensed_egyptologist_specializing_in_tours_excursions.html 1
 
1.8%
https://www.tripadvisor.com//attraction_review-g294201-d4064603-reviews-egypt_tour_guide_mina_samir-cairo_cairo_governorate.html 1
 
1.8%
https://www.tripadvisor.com//attraction_review-g294201-d18313769-reviews-pyramids_land_private_tours-cairo_cairo_governorate.html 1
 
1.8%
https://www.tripadvisor.com//attraction_review-g294201-d25221395-reviews-personalized_egypt_tours-cairo_cairo_governorate.html 1
 
1.8%
https://www.tripadvisor.com//attraction_review-g294201-d3210482-reviews-egypt_day_tours-cairo_cairo_governorate.html 1
 
1.8%
Other values (41) 41
74.5%
2023-08-01T19:08:27.306792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 465
 
7.1%
t 461
 
7.0%
i 411
 
6.3%
r 395
 
6.0%
_ 329
 
5.0%
a 329
 
5.0%
o 324
 
4.9%
w 277
 
4.2%
- 274
 
4.2%
s 269
 
4.1%
Other values (51) 3024
46.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4301
65.6%
Decimal Number 713
 
10.9%
Uppercase Letter 501
 
7.6%
Other Punctuation 440
 
6.7%
Connector Punctuation 329
 
5.0%
Dash Punctuation 274
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 465
10.8%
t 461
10.7%
i 411
9.6%
r 395
 
9.2%
a 329
 
7.6%
o 324
 
7.5%
w 277
 
6.4%
s 269
 
6.3%
v 197
 
4.6%
d 176
 
4.1%
Other values (15) 997
23.2%
Uppercase Letter
ValueCountFrequency (%)
R 115
23.0%
A 68
13.6%
C 60
12.0%
P 43
 
8.6%
G 33
 
6.6%
I 30
 
6.0%
T 30
 
6.0%
F 29
 
5.8%
M 25
 
5.0%
E 19
 
3.8%
Other values (11) 49
9.8%
Decimal Number
ValueCountFrequency (%)
1 138
19.4%
4 103
14.4%
2 98
13.7%
7 92
12.9%
8 70
9.8%
9 65
9.1%
0 55
 
7.7%
3 33
 
4.6%
6 31
 
4.3%
5 28
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/ 220
50.0%
. 165
37.5%
: 55
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 329
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4802
73.2%
Common 1756
 
26.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 465
 
9.7%
t 461
 
9.6%
i 411
 
8.6%
r 395
 
8.2%
a 329
 
6.9%
o 324
 
6.7%
w 277
 
5.8%
s 269
 
5.6%
v 197
 
4.1%
d 176
 
3.7%
Other values (36) 1498
31.2%
Common
ValueCountFrequency (%)
_ 329
18.7%
- 274
15.6%
/ 220
12.5%
. 165
9.4%
1 138
7.9%
4 103
 
5.9%
2 98
 
5.6%
7 92
 
5.2%
8 70
 
4.0%
9 65
 
3.7%
Other values (5) 202
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 465
 
7.1%
t 461
 
7.0%
i 411
 
6.3%
r 395
 
6.0%
_ 329
 
5.0%
a 329
 
5.0%
o 324
 
4.9%
w 277
 
4.2%
- 274
 
4.2%
s 269
 
4.1%
Other values (51) 3024
46.1%

Tripadvisor rank
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.254545
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size880.0 B
2023-08-01T19:08:27.430758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q119.5
median38
Q359.5
95-th percentile82
Maximum90
Range89
Interquartile range (IQR)40

Descriptive statistics

Standard deviation25.743189
Coefficient of variation (CV)0.65580148
Kurtosis-0.95867393
Mean39.254545
Median Absolute Deviation (MAD)21
Skewness0.16794834
Sum2159
Variance662.71178
MonotonicityNot monotonic
2023-08-01T19:08:27.541396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2 3
 
5.5%
40 2
 
3.6%
1 2
 
3.6%
82 2
 
3.6%
54 2
 
3.6%
51 2
 
3.6%
44 2
 
3.6%
61 2
 
3.6%
28 2
 
3.6%
22 2
 
3.6%
Other values (33) 34
61.8%
ValueCountFrequency (%)
1 2
3.6%
2 3
5.5%
4 1
 
1.8%
5 1
 
1.8%
6 1
 
1.8%
7 1
 
1.8%
9 1
 
1.8%
10 1
 
1.8%
11 1
 
1.8%
12 1
 
1.8%
ValueCountFrequency (%)
90 1
1.8%
87 1
1.8%
82 2
3.6%
80 1
1.8%
78 1
1.8%
76 1
1.8%
71 1
1.8%
65 1
1.8%
64 1
1.8%
62 1
1.8%

Interactions

2023-08-01T19:08:20.760797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:05.387592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.004135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.170141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.385365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.608316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.924616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.119526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.320389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.510940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.920703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.272886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.995772image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:05.775549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.210851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.388635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.597112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.823221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.151993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.356377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.561579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.749188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.156682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.513740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.077139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:05.963644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.288887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.471641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.680296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.910248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.248523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.440442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.641411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.836858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.253214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.598587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.188663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:06.239298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.374711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.560826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.780581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.004650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.340127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.533411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.732475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.932946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.342183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.766532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.277172image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:06.463349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.459227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.650692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.876266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.106056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.429550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.620512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.821637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.027180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.428991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.870143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.388713image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:06.668404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.544151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.743658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.993829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.193415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.517884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.712241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.910983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.122914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.566141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.007225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.473247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:06.872354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.637032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.854097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.094730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.280794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.601328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.802079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.996609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.212167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.656707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.112955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.560835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:07.041779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.749568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.942720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.184522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.364533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.686437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.886191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.082182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.297027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.748588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.202682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.643461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:07.200316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.832686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.026768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.264820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.444902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.767838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.968898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.159103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.384721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:18.914682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.330124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.744315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:07.367923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:08.924726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.120523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.359252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.535291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.864181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.063555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.253798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.487032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.018297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.440752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.825669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:07.535473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.006369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.203534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.439152image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.616745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:13.950095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.146276image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.334268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.577791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.103857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.529178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:21.912309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:07.725511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:09.093892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:10.297571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:11.531017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:12.845880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:14.041523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:15.238600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:16.425468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:17.692656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:19.195353image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T19:08:20.624752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-08-01T19:08:27.635953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Reviewers#ExcellentVery goodAveragePoorTerribleExcellent_ratioVG_ratioAverage_ratioPoor_ratioTerrible_ratioTripadvisor rankCityScore
Reviewers#1.0000.1910.002-0.029-0.023-0.0300.046-0.039-0.011-0.034-0.001-0.1530.3080.340
Excellent0.1911.0000.7810.7460.7760.777-0.3500.3330.4910.5170.468-0.6400.0000.000
Very good0.0020.7811.0000.9610.9450.911-0.8110.8010.8310.8050.722-0.2370.0610.501
Average-0.0290.7460.9611.0000.9610.919-0.7780.7660.8850.8290.729-0.2890.3400.401
Poor-0.0230.7760.9450.9611.0000.951-0.7620.7410.8400.8750.768-0.3270.3380.775
Terrible-0.0300.7770.9110.9190.9511.000-0.7080.6740.7660.8130.858-0.3100.1960.742
Excellent_ratio0.046-0.350-0.811-0.778-0.762-0.7081.000-0.992-0.908-0.860-0.768-0.1940.5410.673
VG_ratio-0.0390.3330.8010.7660.7410.674-0.9921.0000.8920.8280.7270.1940.6250.673
Average_ratio-0.0110.4910.8310.8850.8400.766-0.9080.8921.0000.9100.763-0.0380.6990.930
Poor_ratio-0.0340.5170.8050.8290.8750.813-0.8600.8280.9101.0000.855-0.0270.6050.902
Terrible_ratio-0.0010.4680.7220.7290.7680.858-0.7680.7270.7630.8551.0000.0280.3640.822
Tripadvisor rank-0.153-0.640-0.237-0.289-0.327-0.310-0.1940.194-0.038-0.0270.0281.0000.0000.062
City0.3080.0000.0610.3400.3380.1960.5410.6250.6990.6050.3640.0001.0000.596
Score0.3400.0000.5010.4010.7750.7420.6730.6730.9300.9020.8220.0620.5961.000

Missing values

2023-08-01T19:08:22.040019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-01T19:08:22.302384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

CityNamePopular MentionsScoreReviewers#ExcellentVery goodAveragePoorTerribleExcellent_ratioVG_ratioAverage_ratioPoor_ratioTerrible_ratioUrlTripadvisor rank
1CairoTrans travel['memphis tours', 'tour consultant', 'nile cruise', 'wonderful trip', 'travel experience', 'abu simbel', 'dead sea', 'incredible experience', 'egyptian museum', 'every step of the way', 'private tour', 'amazing tour', 'nubian village', 'visit egypt', 'made us feel', 'kom ombo', 'cairo airport', 'always on time', 'his team', 'luxor temple', 'wonderful guide', 'day tour', 'his knowledge', 'felt safe', 'ancient egypt', 'afifi', 'yasmeen', 'itinerary', 'company', 'driver']5.0535535.01.00.00.00.01.0000000.0018690.0000000.0000000.000000https://www.tripadvisor.com//Attraction_Review-g294201-d17462467-Reviews-Trans_travel-Cairo_Cairo_Governorate.html2
2CairoTrans travel['memphis tours', 'tour consultant', 'nile cruise', 'wonderful trip', 'travel experience', 'abu simbel', 'dead sea', 'incredible experience', 'egyptian museum', 'every step of the way', 'private tour', 'amazing tour', 'nubian village', 'visit egypt', 'made us feel', 'kom ombo', 'cairo airport', 'always on time', 'his team', 'luxor temple', 'wonderful guide', 'day tour', 'his knowledge', 'felt safe', 'ancient egypt', 'afifi', 'yasmeen', 'itinerary', 'company', 'driver']5.0535535.01.00.00.00.01.0000000.0018690.0000000.0000000.000000https://www.tripadvisor.com//Attraction_Review-g294201-d17462467-Reviews-Trans_travel-Cairo_Cairo_Governorate.html2
5CairoSahara Travel['tour manager', 'memphis tours', 'nile cruise', 'egyptian museum', 'ahmed osman', 'made us feel', 'abu simbel', 'egypt trip', 'amazing trip', 'cairo airport', 'his passion', 'ancient egypt', 'private tour', 'went smoothly', 'an amazing guide', 'travel company', 'wealth of knowledge', 'special thanks', 'through customs', 'every step', 'the entire trip', 'papyrus shop', 'national museum', 'once in a lifetime', 'answered all of our questions', 'his team', 'took great care', 'day tour', 'amazing country', 'always felt safe']5.0917902.014.01.01.01.00.9836420.0152670.0010910.0010910.001091https://www.tripadvisor.com//Attraction_Review-g294201-d16780499-Reviews-Sahara_Travel-Cairo_Cairo_Governorate.html5
6CairoEgypt Tour Guide - Mina Samir['his team', 'excellent photographer', 'photography skills', 'his knowledge', 'amazing photos', 'cabin crew', 'made us feel', 'papyrus museum', 'solo trip', 'always on time', 'our entire trip', 'taking photos', 'amazing trip', 'giza pyramids', 'arranged everything', 'taking care', 'great guide', 'visit cairo', 'felucca ride', 'answered all our questions', 'nile cruise', 'spent days', 'felt very safe', 'beautiful country', 'ancient history', 'falafel', 'great pyramid', 'samir', 'airport', 'egypt']5.0918914.06.00.00.00.00.9956430.0065360.0000000.0000000.000000https://www.tripadvisor.com//Attraction_Review-g294201-d4064603-Reviews-Egypt_Tour_Guide_Mina_Samir-Cairo_Cairo_Governorate.html6
14CairoPyramids Land Private Tours['egyptian museum', 'takes great pictures', 'skilled driver', 'great tour', 'nice guide', 'essential oils', 'ride camels', 'long layover', 'would highly recommend this tour', 'crazy cairo', 'buy souvenirs', 'booked this tour', 'ancient egypt', 'excellent driver', 'egyptian experience', 'papyrus shop', 'answered all our questions', 'day tour', 'great knowledge', 'cairo tour', 'gouda', 'hoka', 'rasha', 'bazaar', 'pyramids', 'sites', 'mahmoud', 'abu', 'pharmacy', 'egyptologist']5.019441874.046.06.06.013.00.9639920.0236630.0030860.0030860.006687https://www.tripadvisor.com//Attraction_Review-g294201-d18313769-Reviews-Pyramids_Land_Private_Tours-Cairo_Cairo_Governorate.html12
29CairoPersonalized Egypt Tours['photography skills', 'amazing photos', 'his knowledge', 'great photographer', 'professional tour guide', 'brilliant experience', 'civilization museum', 'photo locations', 'highly recommend you book', 'spent several days', 'takes great pictures', 'air conditioned car', 'sultan hassan mosque', 'anyone planning', 'speaks excellent english', 'egypt tours', 'historical facts', 'explaining everything', 'private guide', 'experienced guide', 'touring cairo', 'deep knowledge', 'giza pyramids', 'memorable trip', 'day tour', 'excellent guide', 'felt very safe', 'great tour', 'miro', 'album']5.0114114.00.00.00.00.01.0000000.0000000.0000000.0000000.000000https://www.tripadvisor.com//Attraction_Review-g294201-d25221395-Reviews-Personalized_Egypt_Tours-Cairo_Cairo_Governorate.html22
35CairoEgypt Day Tours['day tour', 'egyptian museum', 'nile cruise', 'his knowledge', 'cairo airport', 'made us feel', 'always on time', 'highly recommend this company', 'beautiful country', 'fantastic tour', 'the entire trip', 'an excellent guide', 'felt safe', 'maro', 'mr', 'alexandria', 'driver', 'pyramids', 'itinerary', 'saqqara', 'osama', 'mo', 'sites', 'representative', 'egyptologist', 'papyrus', 'tipping', 'valley', 'hurghada', 'karnak']5.0917883.033.00.01.00.00.9629230.0359870.0000000.0010910.000000https://www.tripadvisor.com//Attraction_Review-g294201-d3210482-Reviews-Egypt_Day_Tours-Cairo_Cairo_Governorate.html27
36CairoPrivate Tour Guides['highly recommend her to anyone', 'egyptian museum', 'great sense of humor', 'wonderful days', 'day tour', 'coptic area', 'pyramids sphinx', 'egyptian experience', 'ancient egypt', 'local restaurants', 'took great care', 'coptic cairo', 'great photos', 'great tour', 'perfect guide', 'knowledgeable guide', 'spent days', 'amazing trip', 'small group', 'visiting egypt', 'falafel', 'always felt safe', 'once in a lifetime', 'khan el khalili', 'historical sites', 'wealth of knowledge', 'great pyramid', 'made us feel', 'gomaa', 'mona']5.0317309.07.00.00.01.00.9747630.0220820.0000000.0000000.003155https://www.tripadvisor.com//Attraction_Review-g294201-d10794410-Reviews-Private_Tour_Guides-Cairo_Cairo_Governorate.html28
37CairoPrivate Tour Guides['highly recommend her to anyone', 'egyptian museum', 'great sense of humor', 'wonderful days', 'day tour', 'coptic area', 'pyramids sphinx', 'egyptian experience', 'ancient egypt', 'local restaurants', 'took great care', 'coptic cairo', 'great photos', 'great tour', 'perfect guide', 'knowledgeable guide', 'spent days', 'amazing trip', 'small group', 'visiting egypt', 'falafel', 'always felt safe', 'once in a lifetime', 'khan el khalili', 'historical sites', 'wealth of knowledge', 'great pyramid', 'made us feel', 'gomaa', 'mona']5.0317309.07.00.00.01.00.9747630.0220820.0000000.0000000.003155https://www.tripadvisor.com//Attraction_Review-g294201-d10794410-Reviews-Private_Tour_Guides-Cairo_Cairo_Governorate.html28
38CairoRamasside Tours['booking process', 'day tour', 'egyptian museum', 'food tour', 'great tour', 'giza pyramids', 'nile cruise', 'private tour', 'cairo tour', 'camel ride', 'answered all of our questions', 'his knowledge', 'made us feel', 'felt safe', 'the entire trip', 'visit egypt', 'an excellent guide', 'always on time', 'great pyramid', 'ancient egypt', 'mina', 'nada', 'alexandria', 'driver', 'airport', 'company', 'sites', 'ramses', 'itinerary', 'mr']5.024152258.0139.010.05.06.00.9349900.0575570.0041410.0020700.002484https://www.tripadvisor.com//Attraction_Review-g294201-d2263764-Reviews-Ramasside_Tours-Cairo_Cairo_Governorate.html29
CityNamePopular MentionsScoreReviewers#ExcellentVery goodAveragePoorTerribleExcellent_ratioVG_ratioAverage_ratioPoor_ratioTerrible_ratioUrlTripadvisor rank
179ParisGALERIES, JARDINS, ZOO['the natural history museum', 'plants and flowers', 'full bloom', 'nice park', 'animals', 'menagerie', 'botanical', 'plantes', 'benches', 'paleontology', 'joggers', 'stroll', 'glasshouse', 'french', 'seine', 'statues']4.51799875.0679.0150.062.034.00.4863810.3774320.0833800.0344640.018899https://www.tripadvisor.com//Attraction_Review-g187147-d189291-Reviews-GALERIES_JARDINS_ZOO-Paris_Ile_de_France.html59
181Paris7ème Arrondissement['rue cler', 'de mars', 'eiffel tower', 'famous museums', 'market street', 'attractions', 'champs', 'rodin', 'wealthy']4.5279187.081.011.00.00.00.6702510.2903230.0394270.0000000.000000https://www.tripadvisor.com//Attraction_Review-g187147-d188146-Reviews-7eme_Arrondissement-Paris_Ile_de_France.html61
182ParisMusee de la Chasse et de la Nature['stuffed animals', 'modern art', 'animal rights', 'natural world', 'dog collars', 'temporary exhibition', 'amazing museum', 'for sale', 'street art', 'rainy day', 'beautiful building', 'taxidermy', 'weapons', 'rifle', 'owl', 'collection', 'marais', 'unicorn', 'paintings', 'lions', 'mansart', 'fabre', 'interspersed', 'centuries', 'euro', 'louvre']4.5363229.0106.020.04.05.00.6308540.2920110.0550960.0110190.013774https://www.tripadvisor.com//Attraction_Review-g187147-d232162-Reviews-Musee_de_la_Chasse_et_de_la_Nature-Paris_Ile_de_France.html62
184ParisMusee du Parfum - Fragonard['perfume making', 'perfume bottles', 'free tour', 'guided tour', 'for sale', 'paris pass', 'beautiful building', 'shop', 'history', 'museum', 'french', 'france']4.51291781.0346.0107.029.028.00.6049570.2680090.0828810.0224630.021689https://www.tripadvisor.com//Attraction_Review-g187147-d10128174-Reviews-Musee_du_Parfum_Fragonard-Paris_Ile_de_France.html64
185ParisDôme des Invalides['resting place', "napoleon's tomb", 'army museum', 'war heroes', 'french military history', 'buried here', 'golden roof', 'the main attraction', 'magnificent building', 'ticket office', 'eiffel tower', 'church', 'armee', 'vatican', 'mansart', 'architecture', 'reign', 'xiv', 'grandeur', 'gilded', 'louis', 'france', 'jules', 'landmark', 'mass']4.5381218.0132.022.06.03.00.5721780.3464570.0577430.0157480.007874https://www.tripadvisor.com//Attraction_Review-g187147-d189244-Reviews-Dome_des_Invalides-Paris_Ile_de_France.html65
199ParisMusee d'Art Moderne de Paris['permanent collection', 'modern art', 'free museum', 'sonia delaunay', 'major artists', 'eiffel tower', 'nice collection', 'french art', 'de paris', 'works of art', 'beautiful museum', 'dufy', 'exhibition', 'paintings', 'cubist', 'danse', 'realism', 'century', 'technology', 'bookshop', 'cloakroom', 'seine', 'masterpiece', 'arts']4.5740359.0270.068.026.017.00.4851350.3648650.0918920.0351350.022973https://www.tripadvisor.com//Attraction_Review-g187147-d188486-Reviews-Musee_d_Art_Moderne_de_Paris-Paris_Ile_de_France.html80
239SeoulGyeongbokgung Palace['guard ceremony', 'forbidden city in beijing', 'national folk museum', 'joseon dynasty', 'main gate', 'traditional dress', 'free tour', 'free entrance', 'korean history', 'guided tour', 'blue house', 'take pictures', 'walk around', 'south korea', 'visiting seoul', 'hanbok', 'gyeongbokgung', 'architecture', 'tourists', 'backdrop', 'king', 'outfit', 'admission', 'era', 'glimpse', 'performance', 'exit', 'clothing']4.5107555558.04005.01089.086.017.00.5167830.3723850.1012550.0079960.001581https://www.tripadvisor.com//Attraction_Review-g294197-d324888-Reviews-Gyeongbokgung_Palace-Seoul.html1
240SeoulThe War Memorial of Korea['military history', 'outdoor exhibition', 'korean peninsula', 'on display', 'south korea', 'excellent museum', 'huge museum', 'few hours', 'dmz tour', 'exhibits', 'conflict', 'ships', 'artillery', 'samgakji', 'bomber', 'guns', 'tribute', 'soldiers', 'fought', 'helicopter', 'information', 'freedom', 'sacrifice', 'rok', 'replica', 'army', 'invasion', 'flags']4.543072914.01107.0246.029.011.00.6765730.2570230.0571160.0067330.002554https://www.tripadvisor.com//Attraction_Review-g294197-d554537-Reviews-The_War_Memorial_of_Korea-Seoul.html2
303SeoulSeodaemun Prison History Hall['japanese occupation', 'worth a visit', 'learning experience', 'independence', 'torture', 'patriots', 'atrocities', 'displays', 'museum', 'liberation', 'democratic', 'graphic', 'school', 'gate', 'foreigners', 'metro']4.5386167.0174.039.03.03.00.4326420.4507770.1010360.0077720.007772https://www.tripadvisor.com//Attraction_Review-g294197-d1440196-Reviews-Seodaemun_Prison_History_Hall-Seoul.html44
314SeoulSeoul City Wall['wall museum', 'mural village', 'entire length', 'trail', 'gate', 'dongdaemun', 'overview', 'shoes']4.5178100.060.015.03.00.00.5617980.3370790.0842700.0168540.000000https://www.tripadvisor.com//Attraction_Review-g294197-d7717373-Reviews-Seoul_City_Wall-Seoul.html54

Duplicate rows

Most frequently occurring

CityNamePopular MentionsScoreReviewers#ExcellentVery goodAveragePoorTerribleExcellent_ratioVG_ratioAverage_ratioPoor_ratioTerrible_ratioUrlTripadvisor rank# duplicates
0CairoCleopatra Egypt Tours['egypt tours', 'day tour', 'nile cruise', 'private tour', 'tourist guide', 'abu simbel', 'enjoyable trip', 'bucket list', 'made us feel', 'amazing tour', 'white desert', 'national museum', 'kom ombo', 'the entire trip', 'camel ride', 'cairo airport', 'great guide', 'special thanks', 'dream come true', 'felt safe', 'luxor temple', 'his team', 'massimo', 'mr', 'cet', 'itinerary', 'driver', 'company', 'memo', 'alexandria']5.0467457.08.02.00.00.00.9785870.0171310.0042830.00.000000https://www.tripadvisor.com//Attraction_Review-g294201-d2108429-Reviews-Cleopatra_Egypt_Tours-Cairo_Cairo_Governorate.html512
1CairoEgypt Tours Club['egypt tours', 'day tour', 'skillful driver', 'looked after', 'modern times', 'national museum', 'historical information', 'an awesome experience', 'abu simbel', 'private tour', 'nile cruise', 'felt very safe', 'cairo airport', 'giza plateau', 'step pyramid', 'his knowledge', 'islamic cairo', 'camel', 'alexandria', 'race', 'kings', 'valley', 'sites', 'hussein', 'immigration', 'catacombs', 'depth', 'saqqara', 'sellers', 'papyrus']5.0355338.017.00.00.00.00.9521130.0478870.0000000.00.000000https://www.tripadvisor.com//Attraction_Review-g294201-d3547596-Reviews-Egypt_Tours_Club-Cairo_Cairo_Governorate.html822
2CairoPrivate Tour Guides['highly recommend her to anyone', 'egyptian museum', 'great sense of humor', 'wonderful days', 'day tour', 'coptic area', 'pyramids sphinx', 'egyptian experience', 'ancient egypt', 'local restaurants', 'took great care', 'coptic cairo', 'great photos', 'great tour', 'perfect guide', 'knowledgeable guide', 'spent days', 'amazing trip', 'small group', 'visiting egypt', 'falafel', 'always felt safe', 'once in a lifetime', 'khan el khalili', 'historical sites', 'wealth of knowledge', 'great pyramid', 'made us feel', 'gomaa', 'mona']5.0317309.07.00.00.01.00.9747630.0220820.0000000.00.003155https://www.tripadvisor.com//Attraction_Review-g294201-d10794410-Reviews-Private_Tour_Guides-Cairo_Cairo_Governorate.html282
3CairoTrans travel['memphis tours', 'tour consultant', 'nile cruise', 'wonderful trip', 'travel experience', 'abu simbel', 'dead sea', 'incredible experience', 'egyptian museum', 'every step of the way', 'private tour', 'amazing tour', 'nubian village', 'visit egypt', 'made us feel', 'kom ombo', 'cairo airport', 'always on time', 'his team', 'luxor temple', 'wonderful guide', 'day tour', 'his knowledge', 'felt safe', 'ancient egypt', 'afifi', 'yasmeen', 'itinerary', 'company', 'driver']5.0535535.01.00.00.00.01.0000000.0018690.0000000.00.000000https://www.tripadvisor.com//Attraction_Review-g294201-d17462467-Reviews-Trans_travel-Cairo_Cairo_Governorate.html22